Thermoeconomic optimization using an evolutionary algorithm of a trigeneration system driven by a solid oxide fuel cell

A trigeneration system driven by a SOFC (solid oxide fuel cell) is modeled, analyzed and optimized from a thermoeconomic view point. The system includes an absorption refrigeration system to produce cooling and a supplemental heat exchanger for heating. A genetic algorithm is applied to permit multi-objective optimization, and optimal values are obtained for the design parameters (including solid oxide fuel cell inlet temperature, fuel utilization factor, current density and steam-to-carbon ratio). Two objective functions are considered, trigeneration exergy efficiency and the total product unit cost, with the aim of maximizing the trigeneration exergy efficiency and minimizing the total product unit cost. The optimization results achieved with both objectives are compared to help identify the better optimization strategy. The results demonstrate that the optimal design point chosen should be selected from the Pareto optimal solution front. Under optimal conditions, the exergy efficiency and total product unit cost are found to be 48.24% and 25.94 $/GJ, respectively, and it is observed that the maximum exergy destruction occurs in the air heat exchanger and that the solid oxide fuel cell stack has the highest capital investment cost of the system components.